Abstract:

This dissertation uses agent-based simulation to study markets in ways that depart from the Walrasian tradition, and to vindicate Adam Smith’s beliefs about the power of the division of labor to enhance productivity, which mainstream economics has neglected because Walrasian equilibrium is incompatible with nonconvexities such as fixed costs. The first article, “The Invisible Hand, Reloaded,” studies a market in which firms in a commodity market try to maximize profits by estimating demand via an OLS regression, while customers choose the lowest-price firm, but face random firm-specific transactions costs. I call this “empiricist competition.” Near perfect competition emerges with very few firms (e.g., n=3), and the result cross-applies to the free entry case, to U-shaped average costs, and even to (gently) falling average costs, in which case empiricist competition gives rise to a downward-sloping supply curve. The second article, “The Division of Labor is Limited by the Extent of the Market,” vindicates the thesis of Chapter 3 of The Wealth of Nations by building a market of decentralized retailers,
following Howitt and Clower (2000), and then equips agents with avoidable-cost production functions, taste-for-variety utility functions, and techniques to sift through hundreds or thousands of corner solutions to find the optimum behavior when they face buy-sell price spreads and stockout and “jobout” constraints on what they can buy or sell at each price. This gives rise to endogenous specialization, which is compatible with competition yet causes GDP per capita to rise indefinitely with population growth or with the accumulation of “capital” (foregone consumption, subject to diminishing returns and depreciation, which augments labor). What emerges is an interpretation of technological change, not as new discoveries a la Romer (1990), but as the exploration of an already-known technology space which requires sufficient labor-cum-capital to explore. Unlike Romer (1990), this interpretation of technology is a candidate to explain the wealth and poverty of nations. The third article, “Bayesian Skill Reputation Systems," presents a model where agents are endowed with skills whose quality is unobservable and opportunities arrive each turn which can only be exploited by certain skills. I show how agents can use Bayesian updating to derive pretty accurate knowledge about the quality of skills. However, the Bayesian skill reputation system quickly fails when agents can conceal past failures, which suggests a reason why, as Granovetter (1983) showed, networks of “weak ties” are so important for finding jobs, and why employers are suspicious of gaps in resumes.